The influence of learning style on satisfaction and learning effectiveness in the asynchronous web-based learning system

2017 ◽  
Vol 35 (4) ◽  
pp. 473-489 ◽  
Author(s):  
Fei-Fei Cheng ◽  
Chui-Chen Chiu ◽  
Chin-Shan Wu ◽  
Der-Chian Tsaih
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning System ◽  
Learning Effectiveness ◽  
Web Based ◽  
Content Type ◽  
Web Based Learning ◽  
Significant Difference ◽  
E Learning ◽  
The Web

Purpose The purpose of this paper is to investigate the effect of user’s learning style (including accommodators, divergers, convergers, and assimilators) on user’s satisfaction on the web-based learning system and their learning effectiveness. Design/methodology/approach This experimental research used the college students from a technology institute in Taiwan as the subject sources. By using the Kolb’s learning style model, the students are classified as four types of learners: convergers, divergers, assimilators, and accommodators. The authors analyzed the relationships among the different learning styles with their effectiveness of learning and satisfaction of using the web-based learning system. The mediation effect of gender is also presented. Findings This research indicates that: first, the satisfaction of the web-based learning system has significant influence on the learning performance of learners; second, different learning styles learners have no significant effect to the satisfaction on using the web-based learning system; third, learning effectiveness has significant difference among different learning style learners on the web-based learning system; the learning effectiveness of accommodators and divergers was significantly higher than the assimilators; fourth, different learning styles learners show significant difference in gender proportion. In addition to accommodators, whose proportion of women is higher than men, the other three learning styles’ proportions in men are higher than women. Research limitations/implications This study was grounded in the Kolb’s learning style theory. The authors provide implications for academic studies in e-learning research stream that aimed at understanding the role of learning style as well as gender differences in the asynchronous web-based learning system. Practical implications Results from this study provided the implications for students, educators, and e-learning system designers. The design of teaching materials as well as functions of e-learning systems should take learners’ learning style into consideration to ensure the best learning outcome. Originality/value This study examined the students’ learning style as well as gender differences in the asynchronous web-based learning system. An experiment was conducted to ensure the data were collected in a controlled environment, thus, offer the value that most of the prior study lacks.

Towards a Personalized E-Learning System

2011 ◽  
pp. 2124-2134
Author(s):  
Elvis Wai Chung Leung ◽  
Qing Li
Keyword(s):  
Online Education ◽  
Economic Benefit ◽  
Learning System ◽  
Development Cost ◽  
Web Based ◽  
Course Materials ◽  
Web Based Learning ◽  
Interactive Environment ◽  
E Learning ◽  
The Web

To cope with the increasing trend of learning demand and limited resources, most universities are taking advantage of Web-based technology for their distance education or e-learning (Montelpare & Williams, 2000). One of the reasons is due to the significant price drop of personal computers in recent decades; the Internet and multimedia have penetrated into most households. Moreover, most students prefer to learn from an interactive environment through a self-paced style. Under the Web-based learning model, students can learn anytime, anywhere because they are not required to go to school on schedule (Appelt, 1997). Meanwhile, universities also enjoy the economic benefit due to the large student base that can share the development cost of course materials and other operational expenses. Gradually, more and more universities follow this similar way to provide online education.

Adaptation algorithms for selecting personalised learning experience based on learning style and dyslexia type

2019 ◽  
Vol 53 (2) ◽  
pp. 189-200 ◽  
Author(s):  
Aisha Yaquob Alsobhi ◽  
Khaled Hamed Alyoubi
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning Experience ◽  
Assistive Technologies ◽  
Learning Systems ◽  
Learning System ◽  
Fixed Cost ◽  
Learning Material ◽  
Content Type ◽  
E Learning

PurposeThrough harnessing the benefits of the internet, e-learning systems provide flexible learning opportunities that can be delivered at a fixed cost at a time and place to suit the user. As such, e-learning systems can allow students to learn at their own pace while also being suitable for both distance and classroom-based learning activities. Adaptive educational hypermedia systems are e-learning systems that employ artificial intelligence. They deliver personalised online learning interventions that extend electronic learning experiences beyond a mere computerised book through the use of intelligence that adapts the content presented to a user according to a range of factors including individual needs, learning styles and existing knowledge. The purpose of this paper is to describe a novel adaptive e-learning system called dyslexia adaptive e-learning management system (DAELMS). For the purpose of this paper, the term DAELMS will be employed to describe the overall e-learning system that incorporates the required functionality to adapt to students’ learning styles and dyslexia type.Design/methodology/approachThe DAELMS is a complex system that will require a significant amount of time and expertise in knowledge engineering and formatting (i.e. dyslexia type, learning styles, domain knowledge) to develop. One of the most effective methods of approaching this complex task is to formalise the development of a DAELMS that can be applied to different learning styles models and education domains. Four distinct phases of development are proposed for creating the DAELMS. In this paper, we will discuss Phase 3 which is the implementation and some adaption algorithms while in future papers will discuss the other phases.FindingsAn experimental study was conducted to validate the proposed generic methodology and the architecture of the DAELMS. The system has been evaluated by group of university students studying a Computer Science related majors. The evaluation results proves that when the system provide the user with learning materials matches their learning style or dyslexia type it enhances their learning outcomes.Originality/valueThe DAELMS correlates each given dyslexia type with its associated preferred learning style and subsequently adapts the learning material presented to the student. The DAELMS represents an adaptive e-learning system that incorporates several personalisation options including navigation, structure of curriculum, presentation, guidance and assistive technologies that are designed to ensure the learning experience is directly aligned with the user's dyslexia type and associated preferred learning style.

scholarly journals Analysing the relationship between learning styles and navigation behaviour in web-based educational system

2010 ◽  
pp. 400-421 ◽  
Keyword(s):  
Learning Styles ◽  
Computer Science ◽  
Learning Style ◽  
Web Based ◽  
Learning Platform ◽  
Web Based Learning ◽  
Index Of Learning Styles ◽  
Type Indicator ◽  
E Learning ◽  
The Relationship

The aim of our research is to automatically deduce the learning style from the analysis of browsing behaviour. To find how to deduce the learning style, we are investigating, in this paper, the relationships between the learner’s navigation behaviour and his/her learning style in web-based learning. To explore this relation, we carried out an experiment with 27 students of computer science at the engineering school (ESI-Algeria). The students used a hypermedia course on an e-learning platform. The learners’ navigation behaviour is evaluated using a navigation type indicator that we propose and calculate based on trace analysis. The findings are presented with regard to the learning styles measured using the Index of Learning Styles by (Felder and Solomon 1996). We conclude with a discussion of these results.

Towards Best Practices in Web-Based Learning and Teaching

2016 ◽  
pp. 317-332
Author(s):  
Mercy A. Iroaganachi
Keyword(s):  
Best Practices ◽  
Learning Environment ◽  
Learning Styles ◽  
Learning Style ◽  
Learning Objects ◽  
Web Based ◽  
Learning And Teaching ◽  
Web Based Learning ◽  
E Learning ◽  
Level Of Knowledge

The chapter explored best practices in web-based learning and teaching with a view to discover trends and provide valuable information for all in the e-learning environment. It affirms that paradigms in Web-based education have shifted from teacher-centered to learner-centered but basically it remains synchronous or asynchronous. This requires Learning Objects (LOs) to be pedagogically efficient, designed to standard (Multimodal) with designers bearing in mind the varied population and learning styles. LOs are to be personalized thereby creating adaptive content based on learner's abilities, learning style, level of knowledge and preferences. It is recommended that educators have requisite background knowledge and competencies in technology such as hardware, software, and course management systems etcetera. Instructors, designers and all interested persons should consult a checklist of best practices, for assessing learning object repositories. More so, there is need to incorporate hands-on component into the e-learning environment. The chapter provides Indicators for best practices.

Towards a Personalized E-Learning System

2011 ◽  
pp. 1869-1879
Author(s):  
Elvis Wai Chung Leung ◽  
Qing Li
Keyword(s):  
Online Education ◽  
Economic Benefit ◽  
Learning System ◽  
Development Cost ◽  
Web Based ◽  
Course Materials ◽  
Web Based Learning ◽  
Interactive Environment ◽  
E Learning ◽  
The Web

To cope with the increasing trend of learning demand and limited resources, most universities are taking advantage of Web-based technology for their distance education or e-learning (Montelpare & Williams, 2000). One of the reasons is due to the significant price drop of personal computers in recent decades; the Internet and multimedia have penetrated into most households. Moreover, most students prefer to learn from an interactive environment through a self-paced style. Under the Web-based learning model, students can learn anytime, anywhere because they are not required to go to school on schedule (Appelt, 1997). Meanwhile, universities also enjoy the economic benefit due to the large student base that can share the development cost of course materials and other operational expenses. Gradually, more and more universities follow this similar way to provide online education.

An Adaptive E-Learning System based on Student's Learning Styles

2016 ◽  
Vol 14 (3) ◽  
pp. 34-51 ◽  
Author(s):  
Samia Drissi ◽  
Abdelkrim Amirat
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning System ◽  
Educational Materials ◽  
Learning Achievement ◽  
Web Based ◽  
Research Areas ◽  
E Learning ◽  
The Impact

Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia. The main objective was to develop a new Adaptive Educational Hypermedia System based on Honey and Mumford learning style model (AEHS-H&M) and assess the effect of adapting educational materials individualized to the student's learning style. To achieve the main objectives, a case study was developed. An experiment between two groups of students was conducted to evaluate the impact on learning achievement. Inferential statistics were applied to make inferences from the sample data to more general conditions was designed to evaluate the new approach of matching learning materials with learning styles and their influence on student's learning achievement. The findings support the use of learning styles as guideline for adaptation into the adaptive e-learning hypermedia systems.

Antecedents of continued usage intentions of web-based learning management system in Tanzania

2015 ◽  
Vol 57 (7) ◽  
pp. 738-756 ◽  
Author(s):  
Edda Tandi Lwoga ◽  
Mercy Komba
Keyword(s):  
Self Efficacy ◽  
Resistance To Change ◽  
Learning Systems ◽  
Learning System ◽  
Web Based ◽  
Content Type ◽  
Actual Usage ◽  
Web Based Learning ◽  
E Learning ◽  
Learning Management

Purpose – The purpose of this paper is to examine factors that predict students’ continued usage intention of web-based learning management systems (LMS) in Tanzania, with a specific focus on the School of Business of Mzumbe University. Specifically, the study investigated major predictors of actual usage and continued usage intentions of e-learning system, and challenges of using the e-learning system. Design/methodology/approach – Data were collected through a questionnaire survey of 300 third year undergraduate students, with a rate of return of 77 per cent. A total of 20 faculty members were also interviewed. The unified theory of acceptance and use of technology (UTAUT) was utilized in the study. Findings – The results show that actual usage was determined by self-efficacy, while continued usage intentions of web-based learning system was predicted by performance expectancy, effort expectancy, social influence, self-efficacy, and actual usage. Challenges for using web-based LMS were related to information and communications technology (ICT) infrastructure barrier, LMS user interface was not user friendly, weak ICT policies, management and technical support, limited skills, lack of awareness, resistance to change, and lack of time to prepare e-content and use the e-learning system. Practical implications – The study findings are useful to e-learning managers and university management to identify important factors and develop appropriate policies and strategies to encourage long-term usage of e-learning systems for future studies and lifelong learning. Originality/value – By using UTAUT in the context of continued usage intentions and the integration of an additional construct (“self-efficacy”), the extended UTAUT model fits very well in the web-based learning systems in Tanzania, in particular where such studies are scant. The findings can be used in other institutions with similar conditions in investigating the continued usage intentions of e-learning systems.

Effectiveness of web-based learning environment: role of intrinsic learning motivation, computer self-efficacy, and learner engagement

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nimitha Aboobaker ◽  
Muneer K.H.
Keyword(s):  
Learning Environment ◽  
Self Efficacy ◽  
Learning Motivation ◽  
Learning Effectiveness ◽  
Learning Engagement ◽  
Web Based ◽  
Content Type ◽  
Web Based Learning ◽  
Computer Self Efficacy

Purpose In the context of the abrupt shift to technology-enabled distance education, this paper examines the role of intrinsic learning motivation, computer self-efficacy and learning engagement in facilitating higher learning effectiveness in a web-based learning environment. Design/methodology/approach Data was collected using a self-administered online questionnaire from a sample of randomly selected 508 university students from different disciplines, including science, technology, and management. Findings Learning motivation and computer self-efficacy positively influenced students' learning engagement, with computer self-efficacy having a more substantial impact. Proposed mediation hypotheses too were supported. Originality/value The insights gained from this study will help in devising strategies for improving students' learning effectiveness. Game-based learning pedagogy and computer simulations can help students understand the higher meaning and purpose of the learning process.

Knowledge Mining for Adaptive Multimedia Web-Based Educational Platform

2008 ◽  
pp. 205-257 ◽  
Author(s):  
Leyla Zhuhadar ◽  
Olfa Nasraoui ◽  
Robert Wyatt
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Intelligent System ◽  
Learning Material ◽  
Online Information ◽  
Learning Sequence ◽  
Online Students ◽  
User Models ◽  
Web Based ◽  
The Web

This chapter introduces an Adaptive Web-Based Educational platform that maximizes the usefulness of the online information that online students retrieve from the Web. It shows in a data driven format that information has to be personalized and adapted to the needs of individual students; therefore, educational materials need to be tailored to fit these needs: learning styles, prior knowledge of individual students, and recommendations. This approach offers several techniques to present the learning material for different types of learners and for different learning styles. User models (user profiles) are created using a combination of clustering techniques and association rules mining. These models represent the learning technique, learning style, and learning sequence, which can help improve the learning experience on the Web site for new users. Furthermore, the user models can be used to create an intelligent system that provides recommendations for future online students whose profile matches one of the mined profiles that represents the discovered user models.

Design and Implementation of the Web-based Learning System for C Programming Language

2014 ◽  
Vol 20 (12) ◽  
pp. 640-645
Author(s):  
Yeomyeong Woo ◽  
Jiwoong Bang ◽  
Jaemin Song ◽  
Jinyeong Yoo ◽  
Sangjun Lee
Keyword(s):  
Programming Language ◽  
Learning System ◽  
Web Based ◽  
C Programming Language ◽  
Design And Implementation ◽  
Web Based Learning ◽  
C Programming ◽  
The Web
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